• DocumentCode
    1220534
  • Title

    Hellinger Versus Kullback–Leibler Multivariable Spectrum Approximation

  • Author

    Ferrante, Augusto ; Pavon, Michele ; Ramponi, Federico

  • Author_Institution
    Dipt. di Ingegne- ria dell´´Inf., Univ. di Padova, Padova
  • Volume
    53
  • Issue
    4
  • fYear
    2008
  • fDate
    5/1/2008 12:00:00 AM
  • Firstpage
    954
  • Lastpage
    967
  • Abstract
    In this paper, we study a matricial version of a generalized moment problem with degree constraint. We introduce a new metric on multivariable spectral densities induced by the family of their spectral factors, which, in the scalar case, reduces to the Hellinger distance. We solve the corresponding constrained optimization problem via duality theory. A highly nontrivial existence theorem for the dual problem is established in the Byrnes-Lindquist spirit. A matricial Newton-type algorithm is finally provided for the numerical solution of the dual problem. Simulation indicates that the algorithm performs effectively and reliably.
  • Keywords
    Newton method; approximation theory; matrix algebra; optimisation; Byrnes-Lindquist spirit; Hellinger distance; Kullback-Leibler multivariable spectrum approximation; constrained optimization problem; duality theory; generalized moment problem; matricial Newton-type algorithm; multivariable spectral densities; Collaborative work; Constraint optimization; Constraint theory; Entropy; Filters; Interpolation; Multidimensional systems; Optimization methods; Robust control; Signal processing algorithms; Approximation of multivariable power spectra; Hellinger distance; Kullback–Leibler index; convex optimization; matricial descent method;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2008.920238
  • Filename
    4522610